Critical Care Group Research Articles

A Comparative Study of Sub-Specialty Selection Among Adult Cardiology Fellows: Does Gender Play a Role?

Objectives: This study is aimed to determine the factors that influence the selection of sub-specialty training among adult cardiology FITs and whether this differs by gender. Methodology: A multiple-choice online survey was conducted on 198 cardiology Fellows-in-training (FITs) in Pakistan from January-May 2023 to assess the determinants of their career paths in clinical cardiac electrophysiology, interventional cardiology, cardiac imaging, and critical care. The survey tool was used for data collection. Results: A total of 198 FITs completed the survey; 36% anticipated specializing in interventional cardiology (IC), 28% in Electrophysiology (EP), 12% in critical care (CC), 15% in cardiac imaging (CI) and 9% were unsure. Among IC and CC group, there was male FIT dominance (70% and 54% respectively) and likelihood of getting employment after completing training was most important factor in both sub-specialties (P <0.001) . Among EP and CI group, there was predominance of women FIT (76% and 56% respectively). The most important factor that influenced FITs to pursue EP was a strong interest in the field and female role model (P <0.001), while for CI minimal radiation exposure and flexibility in job were important factors (all P<0.001). Conclusion: Female FITs are less inclined to choose interventional cardiology as future career path because of increased radiation exposure and old-boys club. Conversely there is growing trend for female FITS inclination towards choosing Electrophysiology, this is in contrast to similar study conducted internationally.

103: How a Healthcare System Leveraged ICU Patient Load Balancing to Manage the COVID-19 Pandemic Surge

INTRODUCTION: Beth Israel Lahey Health (BILH) formed in March 2019 incorporating 2 legacy systems and 3 independent hospitals In March 2020, during the surge of COVID-19 in MA, BILH formed a Critical Care Group (CCG) to assist patient load balancing and equipment leveling across all 12 hospitals METHODS: CCG members included ICU leaders from 3 tertiary hospitals and the BILH Chief Medical Officer The team huddled twice daily, and developed ICU bed and ventilator surge plans, and pathways for balancing across the network Requests for transfers from referring hospitals were redirected to BILH hospitals with capacity CCG made strategic decisions to transfer patients within BILH so that no single hospital became overwhelmed CCG invited 3 Safety Net Hospitals (SNHs) to the huddles;each SNH was in a COVID ?hotspot,? and the CCG accommodated their transfers RESULTS: The CCG enabled BILH to flex to 238% of the system's baseline 224 licensed ICU beds At peak, BILH's tertiary hospital ICUs had an occupancy at 157% of baseline, with 73% of ICU patients on ventilators From 3/1-6/30, one of the tertiary BILH hospitals accepted 81 SNH ICU transfers;support for SNHs was critical for the overall State response to the surge Unexpected benefits of the CCG included providing a platform for communication and knowledge sharing;discussions included standardization for tracheostomy procedures, management of ECMO resources, avoidance of pitfalls using anesthesia machines as ventilators, and protocols for proning As a new system, these strengthened relationships between legacy hospital systems In addition, MA developed a similar CCG, with the aim of the state's largest hospitals having awareness of how other hospitals' ICUs were managing the surge CONCLUSIONS: CCG was essential to the BILH system as it facilitated a real-time adaptive response to the surge Key elements included: 1) Creating a team of senior Critical Care leadership, all of whom were closely in tune with their respective ICU's current status and needs 2) CCG relied on a dashboard that provided daily data on ICU capacity at each hospital, allowing for real-time decision-making 3) Early planning prior to the influx of patients;the CCG formed when the COVID critical care census system-wide was 5, relative to a census of 190 at peak surge

A lung ultrasound score for early triage of elderly patients with acute dyspnea.

Lung ultrasound has value in diagnosing dyspnea. The main objective of this study was to evaluate the accuracy of a modified lung ultrasound (MLUS) score to predict the severity of acute dyspnea in elderly patients. This was an observational single-centre study including patients over age 64 admitted to the emergency department for acute dyspnea with hypoxia. Participants had an early lung ultrasound performed by a dedicated emergency physician, followed by the usual care by a team blinded to the lung ultrasound results. Patients were allocated by disposition to either a critical care (CC) group (patients who needed admission to the intensive care unit [ICU] and/or who died within 48 h) or a standard care group. Among 137 patients analysed (mean age 79 ± 13 years, 74 [54%] women), 43 (31%) were categorized into the CC group. The time taken to obtain the MLUS was 30 ± 22 min. The area under the receiver operating characteristic curve of the MLUS for predicting the CC group was 0.97 (0.92-0.99; p < 0.01) with a cut-off set strictly above 17 for 93% sensitivity (81-99), 99% specificity (94-100), a positive predictive value of 98% (87-100), a negative predictive value of 97% (91-99), a positive likelihood ratio of 86, a negative likelihood ratio of 0.07, and a diagnostic accuracy of 97% (93-99). In a multivariate analysis, the MLUS was the only independent associated factor for the CC group. An early lung ultrasound score can predict the need for ICU admission and/or death within 48 hours in elderly dyspneic patients.

Occurrence of Clinical Bone Fracture Following a Prolonged Stay in Intensive Care Unit: A Retrospective Controlled Study.

Clinical consequences of critical illness and critical care (CC) on bone health remain largely unexplored. This retrospective study aimed to assess the number of new bone fractures (BF) following a prolonged length of stay (LOS) in intensive care unit (ICU). Adults admitted in our tertiary ICU during 2013 with a stay >7days were included (CC group). Patients who died in ICU or lost to follow-up were excluded. For each CC patient still alive after 2years of follow-up, 2 control patients, scheduled for surgery during 2013, were recruited and matched for gender and age. Basal fracture risk before admission was calculated using FRAX tool. General practitioners were phoned to check out new bone fracture (BF) during 2years after admission. Of the 457 enrolled CC patients, 207 did not meet inclusion criteria and 72 died during FU (median age 72 [65-77]years). New BF occurred in 9 of the 178 patients still alive at the end of FU (5%). Median age of these patients was 64 [53-73]years. Fractured patients did not differ from non-fractured ones based on demographic and clinical characteristics, excepting for FRAX risks that were higher in fractured patients. In the control group, 327 patients were analyzed. Their rate of BF was 3.4% without statistical significance compared to the CC group. FRAX risks were similar in both groups. The risk of new BF in CC group, expressed as an odds ratio, was 50% higher than in the control group without achieving statistical significance (odds ratio 1.53; 95% confidence interval 0.62-3.77; p=0.35). When comparing ICU survivors to patients who underwent uncomplicated surgery in the present preliminary study included limited cohorts, the fracture risk in the 2years following prolonged ICU stay was not statistically higher. However, CC fractured patients had higher FRAX risks than non-fractured patients. Such screening could help to target prevention and appropriate treatment strategies.